Chef Software
Senior Software Engineer
Relus Technologies Feb 2017 - Jul 2017
Senior Cloud Architect
Omniti Dec 2014 - Jan 2017
Devops Practice Lead
Omniti Apr 2011 - Dec 2014
Web Architect
Omniti Jan 1, 2008 - Apr 1, 2011
Web Engineer
Education:
Indiana University Bloomington 1995 - 1998
Bachelors, Bachelor of Arts, Applied Mathematics
Skills:
Postgresql Apache Git Perl Web Development Ruby Web Applications Javascript Subversion Open Source Css Jquery Chef Software Project Management Node.js Front End Xhtml Mysql Web Application Design Ajax
Mark E. Kohan - Downingtown PA, US Clinton J. Wolfe - Malvern PA, US
Assignee:
IMS Software Services Ltd. - Plymouth Meeting PA
International Classification:
G06F 15/167
US Classification:
709212
Abstract:
Systems and processes for assembling de-identified patient healthcare data records in a longitudinal database are provided. The systems and processes may be implemented over multiple data suppliers and common database facilities while ensuring patient privacy. At the data supplier locations, patient-identifying attributes in the data records are placed in standard format and then doubly encrypted using a pair of encryption keys before transmission to a common database facility. The pair of encryption keys includes a key specific to the data supplier and a key specific to the common database facility. At the common database facility, the encryption specific to the data supplier is removed, so that multi-sourced data records have only the common database encryption. Without direct access to patient identifying-information, the encrypted data records are assigned dummy labels or tags by which the data records can be longitudinally linked in the database. The tags are assigned based on statistical matching of the values of a select set of encrypted data attributes with a reference database of tags and associated encrypted data attribute values.
Data Record Matching Algorithms For Longitudinal Patient Level Databases
Mark Kohan - Downingtown PA, US Clinton Wolfe - Malvern PA, US Heather Zuleba - Lafayette Hill PA, US
International Classification:
G06F017/60
US Classification:
705002000
Abstract:
A method is provided for assigning longitudinal linking tags to de-identified patient data records by matching the patient data records with reference data records. The de-identified patient data records may include both encrypted and non-encrypted data attributes. Different possible subsets of the data attributes are categorized in a hierarchy of levels. Subsets of data field values are compared with the reference data records one level at a time. Upon successful comparison or matching of a subset of data field values, a longitudinal linking tag associated with a matched reference data record is assigned to de-identified data record is assigned. When a match is not found, a new longitudinal linking tag is created and assigned to the de-identified data record. The new tag and corresponding data record attributes are then added to the reference data for future matching operations.
Mediated Data Encryption For Longitudinal Patient Level Databases
Mark Kohan - Downingtown PA, US Clinton Wolfe - Malvern PA, US
International Classification:
G06F017/60
US Classification:
705002000
Abstract:
A system and method for the assembly of a longitudinally linked database of patient healthcare data records involve a neutral implementation partner to ensure that sensitive patient-identifying information contained in the data records is secure at all times. The implementation partner is deployed to mediate processing of the data records in a secure environment, which is inaccessible to unauthorized parties including data supplier and database facility personnel. At data supplier sites, the implementation partner mediates processing of the data records so that the patient-identifying attributes in the data records are encrypted before they are transmitted to a common longitudinal database facility. At the common longitudinal database facility, the implementation partner mediates processing of the data records so that internal tags are assigned to data records based on the values of the encrypted patient-identifying attributes. The internal tags are used to longitudinally link the encrypted data records in a statistically meaningful manner. The implementation partner may be any combination of software, hardware and organizational entities.
Data Encryption Applications For Multi-Source Longitudinal Patient-Level Data Integration
Mark Kohan - Downingtown PA, US Clinton Wolfe - Malvern PA, US
International Classification:
G06F017/60
US Classification:
705002000
Abstract:
Software applications are provided for integrating individual multi-sourced patient healthcare transaction data records in a longitudinal database. The data records are processed in a manner which preserves patient privacy by encrypting patient-identifying attributes in the data records and thereby rendering sensitive personal information inaccessible. The applications, which may be organized as modules using common frame work components, are designed to process the multi-sourced data records at data supplier sites and at a common database assembly facility. The applications provide the data supplier sites and the database facility with methods for acquiring attributes, standardizing formats, encryption key generation, and encrypting and decrypting attributes in the data records. The encryption application provides methods for double encryption of the data records at data supplier sites using a key specific to a data supplier and a key specific to the database facility.